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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
18,485 ratings

About the Course

Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models. Topics covered include: - collecting and importing data - cleaning, preparing & formatting data - data frame manipulation - summarizing data - building machine learning regression models - model refinement - creating data pipelines You will learn how to import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. You will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them. In addition to video lectures you will learn and practice using hands-on labs and projects. You will work with several open source Python libraries, including Pandas and Numpy to load, manipulate, analyze, and visualize cool datasets. You will also work with scipy and scikit-learn, to build machine learning models and make predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge....

Top reviews

SC

May 5, 2020

I started this course without any knowledge on Data Analysis with Python, and by the end of the course I was able to understand the basics of Data Analysis, usage of different libraries and functions.

RP

Apr 19, 2019

perfect for beginner level. all the concepts with code and parameter wise have been explained excellently. overall best course in making anyone eager to learn from basics to handle advances with ease.

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2401 - 2425 of 2,890 Reviews for Data Analysis with Python

By Coco

Jan 14, 2020

Quizs could be more practical. The part of explaining models is amazing!

By Manuel O

Aug 21, 2019

Learning may be more beneficially if we actually wrote most of the code.

By Kisha B

Jun 28, 2019

I took this course out of sequence, but it has been the best one so far!

By ZHANG B

Apr 22, 2019

The content in the lab is great! However, video courses are not so good.

By Raphael I

Apr 27, 2021

great course,

exam handling not learner friendly & not very challenging

By shiva m a

Aug 3, 2020

Awesome introduction to data analysis with python. Loved it absolutely!

By Moaz M

Oct 11, 2019

some topics have not been covered well like piplines , cross validation

By David O

Jul 26, 2020

The materials are well-organized, but there are many typos throughout.

By Angeliki M

Dec 2, 2019

A really good course. Probably the best so far in the IBM Certificate.

By Nanjun L

Jan 9, 2019

Would be better if more programming-oriented assignments are provided.

By Rahul P

May 12, 2020

Excellent course with detailed hands-on experience via lab exercises.

By Manas C

Mar 31, 2020

The course covers all the fundamental concepts needed for a beginner.

By Obong G

Feb 19, 2019

Though found the ending modules a bit challenging, its a great course

By Padraig M D

Jun 7, 2020

Quite a challenging course, but very rewarding. I really enjoyed it.

By Charles R

Jun 15, 2023

Probably needs a refresh based on current environments now present.

By mohsin a

Oct 17, 2020

Hands on Labs are awesome .They helped to consolidate my concepts .

By Rohit S P

Apr 25, 2019

Needed a more brief explanation on ridge regression and grid search

By Ninad M K

Jul 14, 2020

It is a great course and it teaches me data analysis with python.

By Liezl M

Jul 13, 2022

One of the best courses I have done is the Data Analysis series.

By Ginger M

Mar 18, 2020

I think that for weeks 4 and 5 the course needs more explanation

By Wen P

Dec 24, 2019

Easy understanding

Good sample and comprehensive

Good for beginner

By Jeff J

Aug 27, 2019

Nicely explained. But many minor mistakes here and there though

By Bashar M

Feb 5, 2019

thank you very much ,this course was very useful and interesting

By Cherif H W A

Dec 14, 2019

as usual the labs are great but the videos could be much better

By Nicholas J F

May 3, 2019

Good content. Still spelling errors and mistakes in some place.